Genpact - Assistant Vice President - Machine Learning

AVP - Machine Learning

Responsibilities :

- Work with Product Managers to understand the Predictive Modeling requirements and Define the Architecture using R, Python, Spark, SQL, Hive, Mahout, Tableau ..etc

- Identify the Supervised/Un Supervised classification, Regression, Rule and Cluster based Statistical Machine Learning algorithms which fit to the required data analysis.

- Selecting features, building and optimizing classifiers using machine learning techniques

- Work with Technical leads to design, build optimized solutions on par with current industry best practices in Processing, cleansing, and verifying the integrity of data used for analysis

- Handle large volumes of data for sample data preparation and test data preparation to apply the ML models using Data Munging / Data wrangling/Mash up Techniques.

- Provide consulting and support for custom development and quality assurance efforts for custom work.

- Provide best practices on R, Spark, Hive,SQL, Python,Tableau and other others.

- Manage development designs across multiple projects to meet project and customer required time lines.

- Define Exploratory Data analysis Approach to analyse data and summarize their main characteristic with visual methods.

Non-Negotiable :

- Proven track record in ML & Predictive analysis using Technologies like R,Spark,Python,Mahout.Hive etc.

- Sound knowledge of Statistical Machine Learning Algorithms for exploratory & predictive data analysis.

- Comfortable in a dynamic atmosphere of a technical organization & well versed with object oriented languages, database design & hands-on experience in writing codes, technical design, architecture reviews & large scale enterprise applications.

- Candidate must be organized and analytical, adept at working in a multiple team's environment, able to design and implement a technical solution, and able to handle multiple priorities in a fast moving environment.

- Experience in Regression, Classification, Clustering Algorithms like Linear Regression, Random Forrest, Decision Tree, Logistic Regression, K-Mean, Naive Bayes, SVM, Decision Forests, etc

- B.Tech / M.Tech /BE in Computer Science, Software Engineering, MIS or equivalent preferred.

- Should have hands-on expertise in some of the following technologies - R, Python, Spark, Mahout,Hive..etc